期刊
ASIAN JOURNAL OF CONTROL
卷 18, 期 2, 页码 447-455出版社
WILEY
DOI: 10.1002/asjc.1074
关键词
Motor-speed control; nonlinear control design (NCD); proportional integral derivative (PID) controller; radial basis function neural network (RBFNN); sequential quadratic programming (SQP)
资金
- Taiwan National Science Council [NSC 100-2221-E-024 - 019 -, NSC 101-2221-E-024 -001 -]
The proportional integral derivative (PID) controller is the most frequently used controller design for industrial applications because of its favorable response and simplicity of adjustment. However, PID manual tuning is traditionally based on engineering experience, and adjusting nonlinear or unknown systems is extremely difficult. In promoting an intelligent controller design theory that can be applied to the control of various systems, this paper proposes a nonlinear control design method that involves determining the optimal solution and obtaining the transfer function of an unknown system by using sequential quadratic programming. In addition, this paper presents a case study of an induction motor V/F speed control to demonstrate the effectiveness of the proposed method based on MATLAB simulation. The results prove that the design of the proposed intelligent PID controller is more robust than traditional controller designs.
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